1. Field of the Invention
The present invention relates generally to video tracking systems and, more particularly, to a method for reacquiring a target in an automated video tracking system.
2. Prior Art
For purposes of this disclosure, automated tracking is defined as the automatic control of the Pan, Tilt and Zoom (PTZ) motors of a movable PTZ camera so as to keep the camera view centered on a designated, moving target. Automated tracking as defined is used in a number of different applications areas, such as surveillance and security monitoring. In this area, the target is usually a human.
Automated tracking systems typically have several parts, target selection, model generation, and camera control. A target needs to be selected for tracking. This can be via an operator or via an automated motion detection module or other intruder detection system. An internal “model” of the appearance of the target is necessary to allow the tracking system to find the target in subsequent images. A camera motion control model is necessary to determine how to move the camera to keep the target in the center of the field of view.
The present disclosure relates to the problem of target selection and more particularly, on reacquiring a target in an ambiguous situation where the automatic tracker loses the selected target. Identification of potential tracking candidates (i.e., a desired target) in a video scene is typically not part of the function of an automated tracking system. For instance, in the area of surveillance, target selection requires a lot of background knowledge about the objective of any surveillance application. What looks “suspicious” in one surveillance application, e.g. a retail store, may not look suspicious in another, e.g. a parking lot.
In some applications, any source of motion is suspicious, e.g., monitoring a warehouse at night. In that case, an intrusion detection sensor, or a motion sensor, could be used to designate a target for tracking. A more sophisticated automatic monitoring system, could be used to designate targets for certain other applications, as long as the rules to select targets can be clearly enumerated and implemented. However, in general, in most commercially available systems, especially in the domain of surveillance, it is expected that a human operator will indicate the target to the tracking system. Some commercial systems have been developed that fully automate the selection of the target, however, these systems are not robust enough to handle all of the realistic and normal cases that may be encountered in all applications, particularly in surveillance. Furthermore, it is not always suitable to allow the tracking system to have full control of selecting the target because it is possible that another moving target may become more interesting to track. Systems having automated target selection frequently run off of the target, mainly because of the uncontrollable environment (e.g., illumination conditions, multiple people, etc.). Generally, the systems which employ automated target selection work better for applications where conditions are more predictable and less likely to change, such as video-conferencing, presentation, and learning and do not work well where conditions are less predictable, such as surveillance.
In the systems which employ manual target selection, the operator selects the target by using a joystick to control the pan and tilt motors of a PTZ camera and possibly even the zoom motor of the PTZ camera. The operator manipulating the joystick needs to be trained to correctly use the joystick because tracking in a three-dimensional environment can be very difficult, especially where the target does not have a predictable path and/or is moving rapidly.
When an operator designates a person in the video image as the tracking system's target, there is a subtle difference in meaning between the operator's and the tracking system's concept of the target. The operator is designating a person as the target, however, the tracking system is simply accepting a region of the image as the target. Because of this, the operator may not be overly fussy about what part of the person he picks, since after all, its clear to any (human) observer which person he or she selects. Furthermore, the tracking system will form a target model based on exactly what image region the operator selected. As it has no independent knowledge of the desired target it cannot generalize beyond what it is told.
Therefore, there is a need in the art for method and apparatus which permits an operator of an automated video tracking system to take control of the same and reacquire a target when the video tracking system encounters a period of difficulty in tracking the target.